determinação do "status" nutricional de nitrogênio no feijoeiro utilizando imagens digitais coloridas determination of nitrogen status in bean plants using color digital images

Clicks: 250
ID: 178139
2007
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Abstract
Este trabalho teve como objetivo avaliar o uso de índices espectrais, retirados de imagens digitais, para discriminar diferentes doses de N no feijoeiro. O trabalho, conduzido em vasos de 8 dm³, teve cinco tratamentos (0; 50; 100; 150 e 200 kg de N ha-1), com dez repetições. As imagens foram adquiridas aos 30; 40 e 50 dias após a emergência. Foram desenvolvidas funções discriminantes quadráticas, tendo como vetores de entrada as médias dos "pixels" de diferentes combinações dos quatro índices espectrais testados. Três diferentes tamanhos de blocos de imagem foram testados 9 x 9; 20 x 20 e 40 x 40 "pixels". Os melhores resultados foram alcançados pelos blocos de 9 x 9 e 20 x 20 "pixels", apresentando classificação 94; 96 e 96% superior à classificação ao acaso para os blocos 9 x 9 "pixels" e 92; 94 e 94% para os blocos 20x20 "pixels" aos 30; 40 e 50 dias após a emergência, respectivamente.
The objective of this work was to evaluate image spectral indices to detect nitrogen levels applied to bean plants. The experiment was in pots with 8 dm³ of soil, five treatments (0; 50; 100; 150 and 200 kg of N ha-1) with ten repetitions. The images were taken at 30; 40 and 50 days after emergence. Quadratic discriminant functions were developed, and the input vector was the average of the pixels from different combinations of four spectral indices. Three different sizes of image blocks were tested: 9 x 9, 20 x 20 and 40 x 40 pixels. The best results were obtained when using the 9 x 9 and 20 x 20 pixels blocks, with classification performance of 94; 96 e 96% better than a random classification for the blocks 9 x 9 pixels and 92; 94 and 94% for the blocks 20 x 20 pixels at 30; 40 e 50 days after emergency, respectively.
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Authors ;Murilo M. Baesso;Francisco de A. de C. Pinto;Daniel M. de Queiroz;Luciano B. de Vieira;Enrique A. Alves
Journal bioorganic and medicinal chemistry letters
Year 2007
DOI
10.1590/S0100-69162007000300022
URL
http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162007000300022
Keywords
precision farming digital image processing

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